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Dataset Overview | National Centers for Environmental Information (NCEI)

NCCOS Assessment: Modeling at-sea density of marine birds to support renewable energy planning on the Pacific Outer Continental Shelf of the contiguous United States (NCEI Accession 0242882)

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This dataset provides seasonal spatial rasters of predicted long-term (1980-2017) density of 33 individual species and 13 taxonomic groups of marine birds throughout the Pacific Outer Continental Shelf (OCS) and adjacent waters off the contiguous United States at 2-km spatial resolution. Two indications of the uncertainty associated with the model predictions are also provided: 1) seasonal spatial layers indicating areas with no survey effort and 2) seasonal spatial rasters of the precision of predicted density of each species/group characterized as its coefficient of variation (CV). Predicted density should always be considered in conjunction with these two indications of uncertainty. This dataset also includes spatial rasters of environmental predictor variables that were used in the predictive modeling.
  • Cite as: Leirness, Jeffery B.; Adams, Josh; Ballance, Lisa T.; Coyne, Michael; Felis, Jonathan J.; Joyce, Trevor; Pereksta, David M.; Winship, Arliss J. (2022). NCCOS Assessment: Modeling at-sea density of marine birds to support renewable energy planning on the Pacific Outer Continental Shelf of the contiguous United States (NCEI Accession 0242882). [indicate subset used]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/xqf2-r853. Accessed [date].
gov.noaa.nodc:0242882
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Distributor NOAA National Centers for Environmental Information
+1-301-713-3277
NCEI.Info@noaa.gov
Dataset Point of Contact NOAA National Centers for Environmental Information
ncei.info@noaa.gov
Time Period 1980-01-01 to 2017-12-31
Spatial Bounding Box Coordinates
West: -131
East: -117.1
South: 29.8
North: 49
Spatial Coverage Map
General Documentation
Associated Resources
Publication Dates
  • publication: 2022-01-06
Data Presentation Form Digital table - digital representation of facts or figures systematically displayed, especially in columns
Dataset Progress Status Complete - production of the data has been completed
Historical archive - data has been stored in an offline storage facility
Data Update Frequency As needed
Supplemental Information
Submission Package ID: 4LFC6T

Methods:
This analysis relied mainly on two types of data: counts of marine birds at sea from sighting surveys and information about the environment in the Pacific OCS region. Sighting datasets were provided by various state and federal agencies, academic institutions, and private organizations. Available spatial information describing the environment in the Pacific OCS region was compiled and synthesized by NCCOS. Environmental data came from a range of sources including remote sensing datasets and an ocean model dataset. Spatial environmental variables were characterized as spatial rasters, with dynamic variables represented by seasonal long-term climatologies. Spatial predictive modeling was applied to the sighting data to account for spatial and temporal heterogeneity in survey effort, platform, and protocol. An ensemble machine-learning technique, component-wise boosting of hierarchical zero-inflated count models, was used to relate the counts of each species or taxonomic group to the environmental predictor variables while accounting for survey heterogeneity and the aggregated nature of sightings. The modeling technique allowed for complex non-linear relationships between response and predictor variables and interacting effects among predictors. Bootstrapping was used to derive estimates of the uncertainty in model predictions. For a complete description of the methods see Leirness et al. (2021).
Purpose Marine birds have the potential to be affected by human activities in the ocean environment such as offshore wind energy development. This project was a partnership between the Bureau of Ocean Energy Management (BOEM), the US Geological Survey (USGS), and the National Oceanic and Atmospheric Administration (NOAA) National Centers for Coastal Ocean Science (NCCOS) through Inter-Agency Agreement Numbers M15PG00009 and M15PG00010 to develop maps of the spatial distributions of marine bird species on the Pacific OCS of the contiguous United States that can be used to inform marine spatial planning in the region and guide future data collection efforts. The analysis relied on 21 unique marine bird sighting datasets provided by the various state and federal agencies, academic institutions, and private organizations. This project was conducted to inform BOEM’s renewable energy policy decisions in the Pacific OCS region. Having the most up-to-date and comprehensive biogeographic information is an important part of BOEM’s process to identify and fill critical data gaps, and to assess the potential direct and indirect impacts of offshore renewable energy development on marine birds. Products from this assessment may also support coastal and ocean management efforts by other local, state and federal agencies working in the Pacific OCS region.
Use Limitations
  • accessLevel: Public
  • Distribution liability: NOAA and NCEI make no warranty, expressed or implied, regarding these data, nor does the fact of distribution constitute such a warranty. NOAA and NCEI cannot assume liability for any damages caused by any errors or omissions in these data. If appropriate, NCEI can only certify that the data it distributes are an authentic copy of the records that were accepted for inclusion in the NCEI archives.
Dataset Citation
  • Cite as: Leirness, Jeffery B.; Adams, Josh; Ballance, Lisa T.; Coyne, Michael; Felis, Jonathan J.; Joyce, Trevor; Pereksta, David M.; Winship, Arliss J. (2022). NCCOS Assessment: Modeling at-sea density of marine birds to support renewable energy planning on the Pacific Outer Continental Shelf of the contiguous United States (NCEI Accession 0242882). [indicate subset used]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/xqf2-r853. Accessed [date].
Cited Authors
Principal Investigators
Collaborators
Contributors
Resource Providers
Points of Contact
Publishers
Acknowledgments
  • Related Funding Agency: US DOC; NOAA; NOS; National Centers for Coastal Ocean Science (NCCOS)
  • Related Funding Agency: US DOI; Bureau of Ocean Energy Management (BOEM)
Theme keywords NODC DATA TYPES THESAURUS NODC OBSERVATION TYPES THESAURUS WMO_CategoryCode
  • oceanography
Global Change Master Directory (GCMD) Science Keywords NCCOS Research Data Type
  • NCCOS Research Data Type > Derived Data Product
  • NCCOS Research Data Type > Geospatial
  • NCCOS Research Data Type > Model
NCCOS Research Keywords
  • NCCOS Research Priority > Marine Spatial Ecology
  • NCCOS Research Topic > Ecological and Biogeographic Assessments
  • Predicted Density
Data Center keywords NODC COLLECTING INSTITUTION NAMES THESAURUS NODC SUBMITTING INSTITUTION NAMES THESAURUS Global Change Master Directory (GCMD) Data Center Keywords
Platform keywords NODC PLATFORM NAMES THESAURUS Global Change Master Directory (GCMD) Platform Keywords ICES/SeaDataNet Ship Codes Keywords Platform
  • Aircraft Commander AC-500 fixed-wing
  • Aircraft Partenavia P-68/P-68-Observer fixed-wing
  • F/V Chellissa
  • F/V Frosti
  • F/V Miss Sue
  • F/V Pacific Fury
  • F/V Piky
  • R/V Almar
  • R/V Bell M. Shimada
  • R/V David Starr Jordan
  • R/V Discoverer
  • R/V Fulmar
  • R/V John H. Martin
  • R/V McArthur
  • R/V McArthur II
  • R/V New Horizon
  • R/V Ocean Starr
  • R/V Researcher
  • R/V Reuben Lasker
  • R/V Robert Gordon Sproul
  • R/V Roger Revelle
  • R/V Sally Ride
  • R/V Tatoosh
Instrument keywords NODC INSTRUMENT TYPES THESAURUS Keywords Instruments
  • Data Analysis
  • Environmental Modeling
  • Models/Analyses
Place keywords NODC SEA AREA NAMES THESAURUS Global Change Master Directory (GCMD) Location Keywords NCCOS Research Location
  • Channel Islands National Marine Sanctuary
  • Cordell Bank National Marine Sanctuary
  • Eastern North Pacific Ocean
  • Greater Farallones National Marine Sanctuary
  • Monterey Bay National Marine Sanctuary
  • NCCOS Research Location > Region gt Pacific Ocean
  • NCCOS Research Location > U.S. States and Territories > California
  • NCCOS Research Location > U.S. States and Territories > Oregon
  • NCCOS Research Location > U.S. States and Territories > Washington
  • Olympic Coast National Marine Sanctuary
  • Pacific Outer Continental Shelf
  • Southern California Bight
Project keywords NCCOS Project Keywords
  • https://coastalscience.noaa.gov/project/marine-bird-distributions-pacific-outer-continental-shelf/
  • https://coastalscience.noaa.gov/project/statistical-modeling-marine-bird-distributions/
Keywords NCEI ACCESSION NUMBER
Use Constraints
  • Cite as: Leirness, Jeffery B.; Adams, Josh; Ballance, Lisa T.; Coyne, Michael; Felis, Jonathan J.; Joyce, Trevor; Pereksta, David M.; Winship, Arliss J. (2022). NCCOS Assessment: Modeling at-sea density of marine birds to support renewable energy planning on the Pacific Outer Continental Shelf of the contiguous United States (NCEI Accession 0242882). [indicate subset used]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/xqf2-r853. Accessed [date].
Access Constraints
  • Use liability: NOAA and NCEI cannot provide any warranty as to the accuracy, reliability, or completeness of furnished data. Users assume responsibility to determine the usability of these data. The user is responsible for the results of any application of this data for other than its intended purpose.
Fees
  • In most cases, electronic downloads of the data are free. However, fees may apply for custom orders, data certifications, copies of analog materials, and data distribution on physical media.
Lineage information for: dataset
Processing Steps
  • 2022-01-06T23:07:46Z - NCEI Accession 0242882 v1.1 was published.
Output Datasets
Lineage information for: dataset
Processing Steps
  • Parameter or Variable: Predicted Density (calculated); Units: None; Observation Category: model output; Sampling Instrument: Models/Analyses > Data Analysis > Environmental Modeling; Sampling and Analyzing Method: Predicted density (proportional to number of individuals / km2) of 33 individual marine bird species and 13 taxonomic groups (Table 4) in up to four seasons (spring: Mar-May; summer: Jun-Aug; fall: Sep-Nov; and winter: Dec-Feb) was modeled using habitat-based spatial predictive modeling. See Leirness et al. (2021) for more details.; Data Quality Method: A data re-sampling technique (non-parametric bootstrapping) was used to estimate the precision of predicted density. Median (50th percentile) bootstrapped predictions were chosen as the best estimate of predicted density. Precision was characterized by the coefficient of variation of bootstrapped predictions (‘CV’). Seasonal spatial layers indicating areas with no survey effort are provided as an additional indication of uncertainty in model predictions. All maps of predicted density and CV were reviewed by experts with experience and knowledge of marine birds in the study area. Experts were from a range of organizations including federal and state government agencies, academic institutions, non-profits, and consultants. Comments and feedback received from the review were incorporated into the project report. See Leirness et al. (2021) for more details..
Acquisition Information (collection)
Instrument
  • visual analysis
Platform
  • NEW HORIZON
  • NOAA Ship Bell M. Shimada
  • NOAA Ship David Starr Jordan
  • NOAA Ship Discoverer
  • NOAA Ship McArthur
  • NOAA Ship McArthur II
  • NOAA Ship Reuben Lasker
  • OCEAN STARR
  • R/V Roger Revelle
  • R/V Sally Ride
  • ROBERT GORDON SPROUL
Last Modified: 2023-08-30T13:17:16Z
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